Multiple Imputation
This is the evaluation of the experiment’s results. The focus of this notebook is multiple imputation in preparation of ordinal CFA.
This notebook expands the master thesis by data analysis and respective code as well as short explanations. This markdown does not replace the thesis, it serves solely as an appendix.
Library Downloads
library(tidyverse)
library(broom)
library(ggplot2)
library(dplyr)
library(finalfit)
library(mice)
library(MASS)Sample Description
First, the final sample is loaded:
getwd()[1] "/Users/lara-aidajopp/Documents/Programming_Stuff/Universität Mannheim/Masterthesis/evaluation"raw_data <- readxl::read_excel("data/raw_data.xlsx", sheet = 2)
glimpse(raw_data)Rows: 131
Columns: 27
$ `NEW CASE NR` <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
$ SD01 <dbl> 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, …
$ SD02 <dbl> 11, 2, 2, 5, 2, 8, 5, 2, 3, 4, 2, 2, 2, 1, 9, 8, 2, 2, 3,…
$ SD04 <dbl> 5, 7, 6, 11, 10, 6, 5, 10, 9, 11, 10, 9, 6, 1, 14, 7, 7, …
$ SD04_14 <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "…
$ SD05 <dbl> 7, 2, 6, 5, 4, 4, 4, 4, 6, 4, 4, 4, 2, 1, 4, 4, 3, 4, 4, …
$ TR01_CP <dbl> 2, 2, 3, 3, 4, 4, 5, 5, 5, 6, 6, 6, 7, 8, 9, 10, 10, 11, …
$ TR01 <dbl> 3, 2, 1, 2, 2, 1, 4, 1, 3, 2, 4, 1, 1, 2, 4, 1, 2, 2, 1, …
$ AC01_01 <dbl> 5, 4, 5, 5, 5, 5, 4, 5, 4, 3, 4, 3, 5, 4, 5, 4, 2, 3, 3, …
$ AC01_02 <dbl> 5, 4, 5, 4, 5, 4, -1, 4, 4, 4, 4, 3, 4, 5, 4, -1, 5, 2, 4…
$ AC01_03 <dbl> 5, 4, 5, 4, 2, 5, 4, 5, 4, 4, 3, 3, 5, 4, -1, 5, 4, 3, 4,…
$ DI01_01 <dbl> 5, 2, 4, 4, 3, 5, 4, 4, -1, 5, 3, 3, 5, 5, -1, 5, 4, 3, 4…
$ DI01_02 <dbl> 5, 1, 1, 1, 1, 1, 5, -1, 5, -1, 4, 3, 5, 4, 4, 3, 1, 3, 1…
$ DI01_03 <dbl> 5, 1, 1, 1, 1, 1, 5, -1, 5, -1, 5, 3, 5, -1, 4, -1, 1, 4,…
$ DI01_04 <dbl> 5, 2, 1, 1, 1, 1, -1, -1, 4, 3, 4, 3, 5, 3, 4, -1, 4, 4, …
$ UI01_01 <dbl> 5, 4, 4, 5, 4, 5, 5, 5, 3, 5, 5, 3, 5, 5, 5, 5, 4, 3, 4, …
$ UI01_02 <dbl> 4, 5, 5, 5, 4, 5, 4, 5, 4, 5, 3, 3, 5, 5, 5, 5, 5, 3, 4, …
$ UI01_03 <dbl> 5, 3, -1, -1, 4, -1, -1, 4, 3, 5, 2, 3, 5, 5, -1, 4, 4, 4…
$ UI01_04 <dbl> 5, 2, 1, 1, 1, 1, -1, -1, 2, 1, 1, 3, 5, 2, 1, -1, 1, 4, …
$ EX01_01 <dbl> 5, 4, 3, 3, -1, 2, -1, 5, 4, 4, 4, 3, 5, 3, 5, 4, 2, -1, …
$ EX01_02 <dbl> 5, 2, 3, 1, 4, 2, -1, 2, 2, 2, 2, 3, 5, 5, 4, 3, 3, 3, 1,…
$ EX01_03 <dbl> 5, 1, 3, 1, -1, 2, -1, 2, 2, 1, 1, 3, 5, 3, 4, 3, 1, 4, 1…
$ EX01_04 <dbl> 5, 1, 1, 1, 1, 2, 4, 1, 4, -1, 4, 3, 4, 5, 4, -1, 1, 2, 1…
$ STARTED <dttm> 2025-09-26 14:11:10, 2025-09-26 15:13:01, 2025-09-26 15:…
$ LASTDATA <dttm> 2025-09-26 14:16:16, 2025-09-26 15:21:43, 2025-09-26 15:…
$ TIME_SUM <dbl> 306, 430, 369, 555, 445, 309, 749, 318, 277, 959, 379, 87…
$ FINISHED <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …As discussed within the thesis, the -1 values need to be replaced by plausible values for multiple imputation. However, they need to be turned into NA values first.
relevant_columns <- c("AC01_01", "AC01_02", "AC01_03", "DI01_01", "DI01_02", "DI01_03", "DI01_04", "UI01_01", "UI01_02", "UI01_03", "UI01_04", "EX01_01", "EX01_02", "EX01_03", "EX01_04")
data_with_NA <- raw_data %>%
mutate(
across(
all_of(relevant_columns), ~ na_if(., -1)
)
)
glimpse(data_with_NA)Rows: 131
Columns: 27
$ `NEW CASE NR` <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
$ SD01 <dbl> 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, …
$ SD02 <dbl> 11, 2, 2, 5, 2, 8, 5, 2, 3, 4, 2, 2, 2, 1, 9, 8, 2, 2, 3,…
$ SD04 <dbl> 5, 7, 6, 11, 10, 6, 5, 10, 9, 11, 10, 9, 6, 1, 14, 7, 7, …
$ SD04_14 <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "…
$ SD05 <dbl> 7, 2, 6, 5, 4, 4, 4, 4, 6, 4, 4, 4, 2, 1, 4, 4, 3, 4, 4, …
$ TR01_CP <dbl> 2, 2, 3, 3, 4, 4, 5, 5, 5, 6, 6, 6, 7, 8, 9, 10, 10, 11, …
$ TR01 <dbl> 3, 2, 1, 2, 2, 1, 4, 1, 3, 2, 4, 1, 1, 2, 4, 1, 2, 2, 1, …
$ AC01_01 <dbl> 5, 4, 5, 5, 5, 5, 4, 5, 4, 3, 4, 3, 5, 4, 5, 4, 2, 3, 3, …
$ AC01_02 <dbl> 5, 4, 5, 4, 5, 4, NA, 4, 4, 4, 4, 3, 4, 5, 4, NA, 5, 2, 4…
$ AC01_03 <dbl> 5, 4, 5, 4, 2, 5, 4, 5, 4, 4, 3, 3, 5, 4, NA, 5, 4, 3, 4,…
$ DI01_01 <dbl> 5, 2, 4, 4, 3, 5, 4, 4, NA, 5, 3, 3, 5, 5, NA, 5, 4, 3, 4…
$ DI01_02 <dbl> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 4, 3, 5, 4, 4, 3, 1, 3, 1…
$ DI01_03 <dbl> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 5, 3, 5, NA, 4, NA, 1, 4,…
$ DI01_04 <dbl> 5, 2, 1, 1, 1, 1, NA, NA, 4, 3, 4, 3, 5, 3, 4, NA, 4, 4, …
$ UI01_01 <dbl> 5, 4, 4, 5, 4, 5, 5, 5, 3, 5, 5, 3, 5, 5, 5, 5, 4, 3, 4, …
$ UI01_02 <dbl> 4, 5, 5, 5, 4, 5, 4, 5, 4, 5, 3, 3, 5, 5, 5, 5, 5, 3, 4, …
$ UI01_03 <dbl> 5, 3, NA, NA, 4, NA, NA, 4, 3, 5, 2, 3, 5, 5, NA, 4, 4, 4…
$ UI01_04 <dbl> 5, 2, 1, 1, 1, 1, NA, NA, 2, 1, 1, 3, 5, 2, 1, NA, 1, 4, …
$ EX01_01 <dbl> 5, 4, 3, 3, NA, 2, NA, 5, 4, 4, 4, 3, 5, 3, 5, 4, 2, NA, …
$ EX01_02 <dbl> 5, 2, 3, 1, 4, 2, NA, 2, 2, 2, 2, 3, 5, 5, 4, 3, 3, 3, 1,…
$ EX01_03 <dbl> 5, 1, 3, 1, NA, 2, NA, 2, 2, 1, 1, 3, 5, 3, 4, 3, 1, 4, 1…
$ EX01_04 <dbl> 5, 1, 1, 1, 1, 2, 4, 1, 4, NA, 4, 3, 4, 5, 4, NA, 1, 2, 1…
$ STARTED <dttm> 2025-09-26 14:11:10, 2025-09-26 15:13:01, 2025-09-26 15:…
$ LASTDATA <dttm> 2025-09-26 14:16:16, 2025-09-26 15:21:43, 2025-09-26 15:…
$ TIME_SUM <dbl> 306, 430, 369, 555, 445, 309, 749, 318, 277, 959, 379, 87…
$ FINISHED <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …In order to find out how much information is missing, the NA values must be counted for all columns from AC01_01 - EX01_04. In addition, the total share of NA values within the answers is calculated.
# First drop the col with also NA but referring to socio demographics and thus, textual information
data_with_NA$SD04_14 <- NULL
# Count the NA values
sum_of_NA <- sum(is.na.data.frame(data_with_NA))
# Count the amount of answers for the relevant_columns
relevant_records <- data_with_NA[, relevant_columns]
#print(relevant_records)
total_relevant_cells <- nrow(relevant_records) * ncol(relevant_records)
print(paste("Amount of all cells with NA values: ", sum_of_NA))[1] "Amount of all cells with NA values: 146"print(paste("Total answers (with NA values): ", total_relevant_cells))[1] "Total answers (with NA values): 1965"print(paste("Relative share of NA values in answers: ", round((sum_of_NA * 100/ total_relevant_cells), 2), "%"))[1] "Relative share of NA values in answers: 7.43 %"df_na <- data.frame(
item = character(),
absolute_amount_of_NA = integer(),
relative_amount_of_NA = numeric()
)
for (col_name in relevant_columns) {
absolute_NA <- sum(is.na(data_with_NA[[col_name]]))
relative_NA <- round(absolute_NA * 100 / nrow(data_with_NA), 2)
df_na <- rbind(df_na, data.frame(
item = col_name,
absolute_amount_of_NA = absolute_NA,
relative_amount_of_NA = relative_NA
))
}
print.data.frame(df_na) item absolute_amount_of_NA relative_amount_of_NA
1 AC01_01 3 2.29
2 AC01_02 25 19.08
3 AC01_03 4 3.05
4 DI01_01 9 6.87
5 DI01_02 9 6.87
6 DI01_03 11 8.40
7 DI01_04 4 3.05
8 UI01_01 2 1.53
9 UI01_02 0 0.00
10 UI01_03 38 29.01
11 UI01_04 8 6.11
12 EX01_01 9 6.87
13 EX01_02 6 4.58
14 EX01_03 12 9.16
15 EX01_04 6 4.58What if all rows with at least one NA value are dropped?
data_without_NA <- data_with_NA %>%
drop_na(all_of(relevant_columns))
print.data.frame(count(data_without_NA, TR01)) TR01 n
1 1 20
2 2 15
3 3 12
4 4 10Only 57 records would remain for the scenario of deletion all -1 containing rows. This would result in a more severe unbalancedness of treatment groups as not even the rule of thumb of Bhattacherjee (2012) for medium effect size would have been met. Moreover, the doubled size of treatment 1 compared to treatment 4 would lead to misleading comparisons due to a lower variety of treatment 4.
However, the fraction of values that are missing as well as the impact of their deletion are only an initial starting point justifying why multiple imputation is required. For multiple imputation, we need to transform the items of each dimension into the data type factor, first. As factors allow us to assign the ordinal character to our data (GeeksforGeeks, 2025), which is required for multiple imputation to apply the correct imputation calculation, i.e., logistic regression (Rubin, 1987).
data_with_fct <- data_with_NA %>%
mutate(
across(all_of(relevant_columns), as.factor)
)
glimpse(data_with_fct)Rows: 131
Columns: 26
$ `NEW CASE NR` <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
$ SD01 <dbl> 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, …
$ SD02 <dbl> 11, 2, 2, 5, 2, 8, 5, 2, 3, 4, 2, 2, 2, 1, 9, 8, 2, 2, 3,…
$ SD04 <dbl> 5, 7, 6, 11, 10, 6, 5, 10, 9, 11, 10, 9, 6, 1, 14, 7, 7, …
$ SD05 <dbl> 7, 2, 6, 5, 4, 4, 4, 4, 6, 4, 4, 4, 2, 1, 4, 4, 3, 4, 4, …
$ TR01_CP <dbl> 2, 2, 3, 3, 4, 4, 5, 5, 5, 6, 6, 6, 7, 8, 9, 10, 10, 11, …
$ TR01 <dbl> 3, 2, 1, 2, 2, 1, 4, 1, 3, 2, 4, 1, 1, 2, 4, 1, 2, 2, 1, …
$ AC01_01 <fct> 5, 4, 5, 5, 5, 5, 4, 5, 4, 3, 4, 3, 5, 4, 5, 4, 2, 3, 3, …
$ AC01_02 <fct> 5, 4, 5, 4, 5, 4, NA, 4, 4, 4, 4, 3, 4, 5, 4, NA, 5, 2, 4…
$ AC01_03 <fct> 5, 4, 5, 4, 2, 5, 4, 5, 4, 4, 3, 3, 5, 4, NA, 5, 4, 3, 4,…
$ DI01_01 <fct> 5, 2, 4, 4, 3, 5, 4, 4, NA, 5, 3, 3, 5, 5, NA, 5, 4, 3, 4…
$ DI01_02 <fct> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 4, 3, 5, 4, 4, 3, 1, 3, 1…
$ DI01_03 <fct> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 5, 3, 5, NA, 4, NA, 1, 4,…
$ DI01_04 <fct> 5, 2, 1, 1, 1, 1, NA, NA, 4, 3, 4, 3, 5, 3, 4, NA, 4, 4, …
$ UI01_01 <fct> 5, 4, 4, 5, 4, 5, 5, 5, 3, 5, 5, 3, 5, 5, 5, 5, 4, 3, 4, …
$ UI01_02 <fct> 4, 5, 5, 5, 4, 5, 4, 5, 4, 5, 3, 3, 5, 5, 5, 5, 5, 3, 4, …
$ UI01_03 <fct> 5, 3, NA, NA, 4, NA, NA, 4, 3, 5, 2, 3, 5, 5, NA, 4, 4, 4…
$ UI01_04 <fct> 5, 2, 1, 1, 1, 1, NA, NA, 2, 1, 1, 3, 5, 2, 1, NA, 1, 4, …
$ EX01_01 <fct> 5, 4, 3, 3, NA, 2, NA, 5, 4, 4, 4, 3, 5, 3, 5, 4, 2, NA, …
$ EX01_02 <fct> 5, 2, 3, 1, 4, 2, NA, 2, 2, 2, 2, 3, 5, 5, 4, 3, 3, 3, 1,…
$ EX01_03 <fct> 5, 1, 3, 1, NA, 2, NA, 2, 2, 1, 1, 3, 5, 3, 4, 3, 1, 4, 1…
$ EX01_04 <fct> 5, 1, 1, 1, 1, 2, 4, 1, 4, NA, 4, 3, 4, 5, 4, NA, 1, 2, 1…
$ STARTED <dttm> 2025-09-26 14:11:10, 2025-09-26 15:13:01, 2025-09-26 15:…
$ LASTDATA <dttm> 2025-09-26 14:16:16, 2025-09-26 15:21:43, 2025-09-26 15:…
$ TIME_SUM <dbl> 306, 430, 369, 555, 445, 309, 749, 318, 277, 959, 379, 87…
$ FINISHED <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …Subsequently, since we are using an ordered Likert scale 1-5 (1 = worst value, 5 = best value) an ordering must be added.
draft_data <- data_with_fct %>%
mutate(
across(
all_of(relevant_columns), ~ordered(., levels = 1:5)
)
)
glimpse(draft_data)Rows: 131
Columns: 26
$ `NEW CASE NR` <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
$ SD01 <dbl> 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, …
$ SD02 <dbl> 11, 2, 2, 5, 2, 8, 5, 2, 3, 4, 2, 2, 2, 1, 9, 8, 2, 2, 3,…
$ SD04 <dbl> 5, 7, 6, 11, 10, 6, 5, 10, 9, 11, 10, 9, 6, 1, 14, 7, 7, …
$ SD05 <dbl> 7, 2, 6, 5, 4, 4, 4, 4, 6, 4, 4, 4, 2, 1, 4, 4, 3, 4, 4, …
$ TR01_CP <dbl> 2, 2, 3, 3, 4, 4, 5, 5, 5, 6, 6, 6, 7, 8, 9, 10, 10, 11, …
$ TR01 <dbl> 3, 2, 1, 2, 2, 1, 4, 1, 3, 2, 4, 1, 1, 2, 4, 1, 2, 2, 1, …
$ AC01_01 <ord> 5, 4, 5, 5, 5, 5, 4, 5, 4, 3, 4, 3, 5, 4, 5, 4, 2, 3, 3, …
$ AC01_02 <ord> 5, 4, 5, 4, 5, 4, NA, 4, 4, 4, 4, 3, 4, 5, 4, NA, 5, 2, 4…
$ AC01_03 <ord> 5, 4, 5, 4, 2, 5, 4, 5, 4, 4, 3, 3, 5, 4, NA, 5, 4, 3, 4,…
$ DI01_01 <ord> 5, 2, 4, 4, 3, 5, 4, 4, NA, 5, 3, 3, 5, 5, NA, 5, 4, 3, 4…
$ DI01_02 <ord> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 4, 3, 5, 4, 4, 3, 1, 3, 1…
$ DI01_03 <ord> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 5, 3, 5, NA, 4, NA, 1, 4,…
$ DI01_04 <ord> 5, 2, 1, 1, 1, 1, NA, NA, 4, 3, 4, 3, 5, 3, 4, NA, 4, 4, …
$ UI01_01 <ord> 5, 4, 4, 5, 4, 5, 5, 5, 3, 5, 5, 3, 5, 5, 5, 5, 4, 3, 4, …
$ UI01_02 <ord> 4, 5, 5, 5, 4, 5, 4, 5, 4, 5, 3, 3, 5, 5, 5, 5, 5, 3, 4, …
$ UI01_03 <ord> 5, 3, NA, NA, 4, NA, NA, 4, 3, 5, 2, 3, 5, 5, NA, 4, 4, 4…
$ UI01_04 <ord> 5, 2, 1, 1, 1, 1, NA, NA, 2, 1, 1, 3, 5, 2, 1, NA, 1, 4, …
$ EX01_01 <ord> 5, 4, 3, 3, NA, 2, NA, 5, 4, 4, 4, 3, 5, 3, 5, 4, 2, NA, …
$ EX01_02 <ord> 5, 2, 3, 1, 4, 2, NA, 2, 2, 2, 2, 3, 5, 5, 4, 3, 3, 3, 1,…
$ EX01_03 <ord> 5, 1, 3, 1, NA, 2, NA, 2, 2, 1, 1, 3, 5, 3, 4, 3, 1, 4, 1…
$ EX01_04 <ord> 5, 1, 1, 1, 1, 2, 4, 1, 4, NA, 4, 3, 4, 5, 4, NA, 1, 2, 1…
$ STARTED <dttm> 2025-09-26 14:11:10, 2025-09-26 15:13:01, 2025-09-26 15:…
$ LASTDATA <dttm> 2025-09-26 14:16:16, 2025-09-26 15:21:43, 2025-09-26 15:…
$ TIME_SUM <dbl> 306, 430, 369, 555, 445, 309, 749, 318, 277, 959, 379, 87…
$ FINISHED <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …A prerequisite to conduct multiple imputation is that the data missing is missing at random (MAR). We already know that only data of the items of transparency are missing (again pointed out below), which is underpinned by the missing values map.
draft_data %>%
missing_plot()
The data set relevant_records is used in the following in order to look for pattern of missingness. A pattern for each item of transparency except UI01_02 can be seen (has no missings). However, since proving the MAR is not the focus of the at hand thesis nor possible at all (Heymans & Twisk, 2022), we stop here with the assumption that MAR is given.
relevant_records <- draft_data[, relevant_columns]
relevant_records %>%
missing_pattern() UI01_02 UI01_01 AC01_01 AC01_03 DI01_04 EX01_02 EX01_04 UI01_04 DI01_01
57 1 1 1 1 1 1 1 1 1
18 1 1 1 1 1 1 1 1 1
12 1 1 1 1 1 1 1 1 1
4 1 1 1 1 1 1 1 1 1
2 1 1 1 1 1 1 1 1 1
2 1 1 1 1 1 1 1 1 1
2 1 1 1 1 1 1 1 1 1
2 1 1 1 1 1 1 1 1 1
2 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 0
2 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 1 1 0 1
2 1 1 1 1 1 1 1 0 1
1 1 1 1 1 1 1 0 1 1
2 1 1 1 1 1 1 0 1 1
1 1 1 1 1 1 1 0 1 1
1 1 1 1 1 1 0 1 1 1
1 1 1 1 1 1 0 1 1 1
1 1 1 1 1 1 0 1 1 1
1 1 1 1 1 1 0 1 0 1
1 1 1 1 1 1 0 0 1 1
1 1 1 1 1 0 1 1 1 1
1 1 1 1 1 0 1 1 0 1
1 1 1 1 1 0 1 0 0 1
1 1 1 1 1 0 0 1 0 1
2 1 1 1 0 1 1 1 1 0
1 1 1 0 1 1 1 1 1 1
1 1 1 0 1 1 1 1 1 1
1 1 0 1 0 1 1 1 1 0
1 1 0 0 0 1 1 1 0 0
0 2 3 4 4 6 6 8 9
DI01_02 EX01_01 DI01_03 EX01_03 AC01_02 UI01_03
57 1 1 1 1 1 1 0
18 1 1 1 1 1 0 1
12 1 1 1 1 0 1 1
4 1 1 1 1 0 0 2
2 1 1 1 0 1 1 1
2 1 1 0 1 1 1 1
2 1 0 1 1 1 1 1
2 1 0 1 1 1 0 2
2 1 0 1 0 1 1 2
1 0 1 1 1 1 1 1
1 0 1 0 1 1 1 2
1 0 1 0 1 0 0 4
1 1 1 1 1 1 1 1
2 1 1 1 1 0 1 2
1 1 1 1 1 0 0 3
1 1 1 1 0 1 0 3
1 1 1 1 1 1 1 1
2 1 1 1 1 1 0 2
1 1 1 1 1 1 1 1
2 0 1 0 1 1 1 3
1 0 1 0 0 1 0 5
1 1 1 1 0 0 1 3
1 1 0 1 0 1 1 3
1 0 1 1 1 1 1 2
1 1 1 0 0 1 0 5
1 0 1 0 0 1 0 6
1 1 1 1 1 1 0 2
1 0 1 0 1 1 1 4
1 1 1 0 1 0 1 5
1 1 0 1 0 0 0 7
2 1 1 1 1 1 0 3
1 1 1 1 1 1 1 1
1 1 1 1 1 1 0 2
1 1 1 1 1 0 1 4
1 1 0 1 0 0 0 9
9 9 11 12 25 38 146
Next, we can start the first imputation using the package mice. According to Van Buuren and Groothuis-Oudshoorn (2011), a dry run is recommended “with the maximum number of iterations maxit set to zero” [p. 35]. With this we can check the method used, the predictor matrix, and various other parts as seen below.
ini <- mice(draft_data, maxit = 0)
ini_meth <- ini$method
ini_pred <- ini$predictorMatrix
ini_post <- ini$post
ini_visitS <- ini$visitSequence
ini_seed <- ini$seed
print(ini_meth)NEW CASE NR SD01 SD02 SD04
"" "" "" ""
SD05 TR01_CP TR01 AC01_01
"" "" "" "polr"
AC01_02 AC01_03 DI01_01 DI01_02
"polr" "polr" "polr" "polr"
DI01_03 DI01_04 UI01_01 UI01_02
"polr" "polr" "polr" ""
UI01_03 UI01_04 EX01_01 EX01_02
"polr" "polr" "polr" "polr"
EX01_03 EX01_04 STARTED LASTDATA
"polr" "polr" "" ""
TIME_SUM FINISHED
"" "" print(ini_pred) NEW CASE NR SD01 SD02 SD04 SD05 TR01_CP
NEW CASE NR 0 1 1 1 1 1
SD01 1 0 1 1 1 1
SD02 1 1 0 1 1 1
SD04 1 1 1 0 1 1
SD05 1 1 1 1 0 1
TR01_CP 1 1 1 1 1 0
TR01 1 1 1 1 1 1
AC01_01 1 1 1 1 1 1
AC01_02 1 1 1 1 1 1
AC01_03 1 1 1 1 1 1
DI01_01 1 1 1 1 1 1
DI01_02 1 1 1 1 1 1
DI01_03 1 1 1 1 1 1
DI01_04 1 1 1 1 1 1
UI01_01 1 1 1 1 1 1
UI01_02 1 1 1 1 1 1
UI01_03 1 1 1 1 1 1
UI01_04 1 1 1 1 1 1
EX01_01 1 1 1 1 1 1
EX01_02 1 1 1 1 1 1
EX01_03 1 1 1 1 1 1
EX01_04 1 1 1 1 1 1
STARTED 1 1 1 1 1 1
LASTDATA 1 1 1 1 1 1
TIME_SUM 1 1 1 1 1 1
FINISHED 1 1 1 1 1 1
TR01 AC01_01 AC01_02 AC01_03 DI01_01
NEW CASE NR 1 1 1 1 1
SD01 1 1 1 1 1
SD02 1 1 1 1 1
SD04 1 1 1 1 1
SD05 1 1 1 1 1
TR01_CP 1 1 1 1 1
TR01 0 1 1 1 1
AC01_01 1 0 1 1 1
AC01_02 1 1 0 1 1
AC01_03 1 1 1 0 1
DI01_01 1 1 1 1 0
DI01_02 1 1 1 1 1
DI01_03 1 1 1 1 1
DI01_04 1 1 1 1 1
UI01_01 1 1 1 1 1
UI01_02 1 1 1 1 1
UI01_03 1 1 1 1 1
UI01_04 1 1 1 1 1
EX01_01 1 1 1 1 1
EX01_02 1 1 1 1 1
EX01_03 1 1 1 1 1
EX01_04 1 1 1 1 1
STARTED 1 1 1 1 1
LASTDATA 1 1 1 1 1
TIME_SUM 1 1 1 1 1
FINISHED 1 1 1 1 1
DI01_02 DI01_03 DI01_04 UI01_01 UI01_02
NEW CASE NR 1 1 1 1 1
SD01 1 1 1 1 1
SD02 1 1 1 1 1
SD04 1 1 1 1 1
SD05 1 1 1 1 1
TR01_CP 1 1 1 1 1
TR01 1 1 1 1 1
AC01_01 1 1 1 1 1
AC01_02 1 1 1 1 1
AC01_03 1 1 1 1 1
DI01_01 1 1 1 1 1
DI01_02 0 1 1 1 1
DI01_03 1 0 1 1 1
DI01_04 1 1 0 1 1
UI01_01 1 1 1 0 1
UI01_02 1 1 1 1 0
UI01_03 1 1 1 1 1
UI01_04 1 1 1 1 1
EX01_01 1 1 1 1 1
EX01_02 1 1 1 1 1
EX01_03 1 1 1 1 1
EX01_04 1 1 1 1 1
STARTED 1 1 1 1 1
LASTDATA 1 1 1 1 1
TIME_SUM 1 1 1 1 1
FINISHED 1 1 1 1 1
UI01_03 UI01_04 EX01_01 EX01_02 EX01_03
NEW CASE NR 1 1 1 1 1
SD01 1 1 1 1 1
SD02 1 1 1 1 1
SD04 1 1 1 1 1
SD05 1 1 1 1 1
TR01_CP 1 1 1 1 1
TR01 1 1 1 1 1
AC01_01 1 1 1 1 1
AC01_02 1 1 1 1 1
AC01_03 1 1 1 1 1
DI01_01 1 1 1 1 1
DI01_02 1 1 1 1 1
DI01_03 1 1 1 1 1
DI01_04 1 1 1 1 1
UI01_01 1 1 1 1 1
UI01_02 1 1 1 1 1
UI01_03 0 1 1 1 1
UI01_04 1 0 1 1 1
EX01_01 1 1 0 1 1
EX01_02 1 1 1 0 1
EX01_03 1 1 1 1 0
EX01_04 1 1 1 1 1
STARTED 1 1 1 1 1
LASTDATA 1 1 1 1 1
TIME_SUM 1 1 1 1 1
FINISHED 1 1 1 1 1
EX01_04 STARTED LASTDATA TIME_SUM
NEW CASE NR 1 1 1 1
SD01 1 1 1 1
SD02 1 1 1 1
SD04 1 1 1 1
SD05 1 1 1 1
TR01_CP 1 1 1 1
TR01 1 1 1 1
AC01_01 1 1 1 1
AC01_02 1 1 1 1
AC01_03 1 1 1 1
DI01_01 1 1 1 1
DI01_02 1 1 1 1
DI01_03 1 1 1 1
DI01_04 1 1 1 1
UI01_01 1 1 1 1
UI01_02 1 1 1 1
UI01_03 1 1 1 1
UI01_04 1 1 1 1
EX01_01 1 1 1 1
EX01_02 1 1 1 1
EX01_03 1 1 1 1
EX01_04 0 1 1 1
STARTED 1 0 1 1
LASTDATA 1 1 0 1
TIME_SUM 1 1 1 0
FINISHED 1 1 1 1
FINISHED
NEW CASE NR 0
SD01 0
SD02 0
SD04 0
SD05 0
TR01_CP 0
TR01 0
AC01_01 0
AC01_02 0
AC01_03 0
DI01_01 0
DI01_02 0
DI01_03 0
DI01_04 0
UI01_01 0
UI01_02 0
UI01_03 0
UI01_04 0
EX01_01 0
EX01_02 0
EX01_03 0
EX01_04 0
STARTED 0
LASTDATA 0
TIME_SUM 0
FINISHED 0print(ini_post)NEW CASE NR SD01 SD02 SD04
"" "" "" ""
SD05 TR01_CP TR01 AC01_01
"" "" "" ""
AC01_02 AC01_03 DI01_01 DI01_02
"" "" "" ""
DI01_03 DI01_04 UI01_01 UI01_02
"" "" "" ""
UI01_03 UI01_04 EX01_01 EX01_02
"" "" "" ""
EX01_03 EX01_04 STARTED LASTDATA
"" "" "" ""
TIME_SUM FINISHED
"" "" print(ini_visitS) [1] "NEW CASE NR" "SD01" "SD02"
[4] "SD04" "SD05" "TR01_CP"
[7] "TR01" "AC01_01" "AC01_02"
[10] "AC01_03" "DI01_01" "DI01_02"
[13] "DI01_03" "DI01_04" "UI01_01"
[16] "UI01_02" "UI01_03" "UI01_04"
[19] "EX01_01" "EX01_02" "EX01_03"
[22] "EX01_04" "STARTED" "LASTDATA"
[25] "TIME_SUM" "FINISHED" print(ini_seed)[1] NAThe default method is set to “polr”, i.e., the ordered factors are recognized correctly, thus, this method is used in the actual imputation.
The seed is set to NA, but a seed has to be set for replicability purposes which is done subsequently.
The default predictor matrix is enhanced by the method quickpred() (Van Buuren and Groothuis-Oudshoorn, 2011), which follows the rules for predictor selection introduced by Van Buuren, Boshuizen and Knook (1999). Besides, we are explicitly excluding and including parameters which is not done by quickpred() (Van Buuren and Groothuis-Oudshoorn, 2011), but recommended by Van Buuren, Boshuizen and Knook (1999).
Excluded parameters: NEW CASE NR, TR01_CP, FINISHED Why?: Those parameters are system values that are not selected nor influenced by the user at all except for FINISHED which inherits the same value for all records, i.e., has no significant meaning at all.
Explicitly included parameters: SD01 - SD05, TR01, STARTED, LASTDATA, TIME_SUM Why?: With the MAR assumption, we assume that the responses are influenced by different matters, e.g., socio demographical background and assigned treatment. Moreover, the completion time and further time-specific data might enhance the view of a person and their behavior, e.g., digital familiarness.
Quick remark: “A value of 1 indicates that the column variable is used as a predictor to impute the target (row) variable, and a 0 means that it is not used.” (Van Buuren and Groothuis-Oudshoorn, 2011, p. 19).
predictorMatrix <- quickpred(draft_data, include = c("SD01", "SD02", "SD04", "SD05", "TR01", "STARTED", "LASTDATA", "TIME_SUM"), exclude = c("NEW CASE NR", "TR01_CP", "FINISHED"))
print(predictorMatrix) NEW CASE NR SD01 SD02 SD04 SD05 TR01_CP
NEW CASE NR 0 0 0 0 0 0
SD01 0 0 0 0 0 0
SD02 0 0 0 0 0 0
SD04 0 0 0 0 0 0
SD05 0 0 0 0 0 0
TR01_CP 0 0 0 0 0 0
TR01 0 0 0 0 0 0
AC01_01 0 1 1 1 1 0
AC01_02 0 1 1 1 1 0
AC01_03 0 1 1 1 1 0
DI01_01 0 1 1 1 1 0
DI01_02 0 1 1 1 1 0
DI01_03 0 1 1 1 1 0
DI01_04 0 1 1 1 1 0
UI01_01 0 1 1 1 1 0
UI01_02 0 0 0 0 0 0
UI01_03 0 1 1 1 1 0
UI01_04 0 1 1 1 1 0
EX01_01 0 1 1 1 1 0
EX01_02 0 1 1 1 1 0
EX01_03 0 1 1 1 1 0
EX01_04 0 1 1 1 1 0
STARTED 0 0 0 0 0 0
LASTDATA 0 0 0 0 0 0
TIME_SUM 0 0 0 0 0 0
FINISHED 0 0 0 0 0 0
TR01 AC01_01 AC01_02 AC01_03 DI01_01
NEW CASE NR 0 0 0 0 0
SD01 0 0 0 0 0
SD02 0 0 0 0 0
SD04 0 0 0 0 0
SD05 0 0 0 0 0
TR01_CP 0 0 0 0 0
TR01 0 0 0 0 0
AC01_01 1 0 1 1 1
AC01_02 1 1 0 1 1
AC01_03 1 1 1 0 1
DI01_01 1 1 1 1 0
DI01_02 1 1 0 0 0
DI01_03 1 0 0 0 1
DI01_04 1 0 0 1 1
UI01_01 1 1 1 1 1
UI01_02 0 0 0 0 0
UI01_03 1 1 1 1 1
UI01_04 1 1 1 1 0
EX01_01 1 1 0 0 0
EX01_02 1 1 0 0 1
EX01_03 1 0 1 0 1
EX01_04 1 0 0 0 1
STARTED 0 0 0 0 0
LASTDATA 0 0 0 0 0
TIME_SUM 0 0 0 0 0
FINISHED 0 0 0 0 0
DI01_02 DI01_03 DI01_04 UI01_01 UI01_02
NEW CASE NR 0 0 0 0 0
SD01 0 0 0 0 0
SD02 0 0 0 0 0
SD04 0 0 0 0 0
SD05 0 0 0 0 0
TR01_CP 0 0 0 0 0
TR01 0 0 0 0 0
AC01_01 1 1 0 1 1
AC01_02 0 0 1 1 1
AC01_03 0 1 1 1 1
DI01_01 0 1 1 1 1
DI01_02 0 1 1 1 1
DI01_03 1 0 1 1 1
DI01_04 1 1 0 1 0
UI01_01 1 1 1 0 1
UI01_02 0 0 0 0 0
UI01_03 0 0 1 1 1
UI01_04 1 1 1 1 1
EX01_01 1 1 0 0 1
EX01_02 1 1 1 1 0
EX01_03 1 1 1 0 1
EX01_04 1 1 1 1 1
STARTED 0 0 0 0 0
LASTDATA 0 0 0 0 0
TIME_SUM 0 0 0 0 0
FINISHED 0 0 0 0 0
UI01_03 UI01_04 EX01_01 EX01_02 EX01_03
NEW CASE NR 0 0 0 0 0
SD01 0 0 0 0 0
SD02 0 0 0 0 0
SD04 0 0 0 0 0
SD05 0 0 0 0 0
TR01_CP 0 0 0 0 0
TR01 0 0 0 0 0
AC01_01 1 1 0 1 0
AC01_02 1 1 1 0 1
AC01_03 1 0 0 0 1
DI01_01 1 0 0 1 1
DI01_02 0 1 1 1 1
DI01_03 0 1 1 1 1
DI01_04 1 1 0 1 1
UI01_01 1 1 0 1 1
UI01_02 0 0 0 0 0
UI01_03 0 1 0 1 1
UI01_04 1 0 1 1 1
EX01_01 0 1 0 0 1
EX01_02 1 1 1 0 1
EX01_03 1 1 1 1 0
EX01_04 1 1 1 1 1
STARTED 0 0 0 0 0
LASTDATA 0 0 0 0 0
TIME_SUM 0 0 0 0 0
FINISHED 0 0 0 0 0
EX01_04 STARTED LASTDATA TIME_SUM
NEW CASE NR 0 0 0 0
SD01 0 0 0 0
SD02 0 0 0 0
SD04 0 0 0 0
SD05 0 0 0 0
TR01_CP 0 0 0 0
TR01 0 0 0 0
AC01_01 0 1 1 1
AC01_02 0 1 1 1
AC01_03 0 1 1 1
DI01_01 1 1 1 1
DI01_02 1 1 1 1
DI01_03 1 1 1 1
DI01_04 1 1 1 1
UI01_01 1 1 1 1
UI01_02 0 0 0 0
UI01_03 1 1 1 1
UI01_04 1 1 1 1
EX01_01 1 1 1 1
EX01_02 1 1 1 1
EX01_03 1 1 1 1
EX01_04 0 1 1 1
STARTED 0 0 0 0
LASTDATA 0 0 0 0
TIME_SUM 0 0 0 0
FINISHED 0 0 0 0
FINISHED
NEW CASE NR 0
SD01 0
SD02 0
SD04 0
SD05 0
TR01_CP 0
TR01 0
AC01_01 0
AC01_02 0
AC01_03 0
DI01_01 0
DI01_02 0
DI01_03 0
DI01_04 0
UI01_01 0
UI01_02 0
UI01_03 0
UI01_04 0
EX01_01 0
EX01_02 0
EX01_03 0
EX01_04 0
STARTED 0
LASTDATA 0
TIME_SUM 0
FINISHED 0Now, that the predictor matrix is set, we compute the first actual imputations. To ensure replicability, a seed is set. (Van Buuren and Groothuis-Oudshoorn, 2011) The m value is set to 10 according to the rule of thumb of Rubin (1987). With m = 10 a pilot imputation is conducted in a first place in line with the approach of Von Hippel (2020). The amount of iterations is set to 10 for analysis purposes, e.g., plot examination.
set.seed(1001)
pilot_imp <- mice(draft_data, predictorMatrix = predictorMatrix, maxit = 10, method = ini_meth, m = 10, seed = 1001)
iter imp variable
1 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04To ensure that the MI has converged, we are plotting the mids object. It can be seen that the variability of means and SDs for each item stabilizes, i.e., converges. The only item that is less stabilized at first sight is UI01_01. However, this might lead from the fact that only two values are missing. A similar behavior can be inspected for AC01_01, AC03_03, and DI01_04 as they inherit a similar amount of NA values (3, 4, 4) as UI01_01 (2).
relevant_imputed_col <- c("AC01_01", "AC01_02", "AC01_03", "DI01_01", "DI01_02", "DI01_03", "DI01_04", "UI01_01", "UI01_03", "UI01_04", "EX01_01", "EX01_02", "EX01_03", "EX01_04")
plot(pilot_imp, c(relevant_imputed_col))
Since imputation has worked out, the imputed values are inspected against their plausibility. According to Van Buuren and Groothuis-Oudshoorn (2011) “a good imputed value is a values that could have been observed had it not been missing.” [p. 42]. Thus, the densities of all values (observed and imputed ones) of the variables that have been imputed are depicted below.
vars <- relevant_imputed_col
stripplot(pilot_imp, as.formula(paste("~", paste(vars, collapse = " + "))), layout = c(1, 1), xlim = c(0, 6))
It can be seen that only plausible values are imputed If the observed values (blue) are scattered across 1 to 5, the imputed ones (red) are, too. Especially in UI01_01 it can be observed that the imputation aligns with the observation, i.e., only values between 2 to 5 were observed and only values between 2 to 5 were imputed.
Now that the first pilot is finished, it must be analyzed if the current m achieves an acceptable fraction of missing information (FMI). If this is the case, the imputed object will be used for ordinal CFA and subsequently, for (M)ANOVA.
Since, we only aim to calculate it exemplary in order to adjust the m of imputations, the FMI is calculated for the sum of all imputed items, i.e., the total score (Heymans and Eekhout, 2019). This is also in line with the observations of Carifio and Perla (2007) stating that Likert scales behave approximately continuous on the macro level, i.e., if the sum of items is conducted. As all imputed items share the same predictors, predictors with the same data type are used in the formula consisting of treatment, socio demographic, and time-related information.
On the basis of the resulting FMI value, the m is kept or set for the actual multiple imputation based on the quadratic rule observations of Bodner (2008) which are also outlined graphically and in numbers by Von Hippel (2018). Since is founded on continuous data and in the at hand paper we conduct approximately continuous data, we assume that the quadratic rule observations also apply in the at hand case for the total mean of imputed items.
pilot_extracted <- complete(pilot_imp, include = TRUE, action = "long")
pilot_extracted$UI01_02 <- NULL
pilot_extracted_mutated <- pilot_extracted %>%
mutate(
across(
all_of(relevant_imputed_col), ~as.integer(.x)
)
)
pilot_extracted_mutated <- pilot_extracted %>%
mutate(
total_score_imputed_items =
rowMeans(
pilot_extracted_mutated[, (relevant_imputed_col)], na.rm = TRUE
)
)
glimpse(pilot_extracted_mutated)Rows: 1,441
Columns: 28
$ `NEW CASE NR` <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,…
$ SD01 <dbl> 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, …
$ SD02 <dbl> 11, 2, 2, 5, 2, 8, 5, 2, 3, 4, 2, 2, 2, 1,…
$ SD04 <dbl> 5, 7, 6, 11, 10, 6, 5, 10, 9, 11, 10, 9, 6…
$ SD05 <dbl> 7, 2, 6, 5, 4, 4, 4, 4, 6, 4, 4, 4, 2, 1, …
$ TR01_CP <dbl> 2, 2, 3, 3, 4, 4, 5, 5, 5, 6, 6, 6, 7, 8, …
$ TR01 <dbl> 3, 2, 1, 2, 2, 1, 4, 1, 3, 2, 4, 1, 1, 2, …
$ AC01_01 <ord> 5, 4, 5, 5, 5, 5, 4, 5, 4, 3, 4, 3, 5, 4, …
$ AC01_02 <ord> 5, 4, 5, 4, 5, 4, NA, 4, 4, 4, 4, 3, 4, 5,…
$ AC01_03 <ord> 5, 4, 5, 4, 2, 5, 4, 5, 4, 4, 3, 3, 5, 4, …
$ DI01_01 <ord> 5, 2, 4, 4, 3, 5, 4, 4, NA, 5, 3, 3, 5, 5,…
$ DI01_02 <ord> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 4, 3, 5, 4…
$ DI01_03 <ord> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 5, 3, 5, N…
$ DI01_04 <ord> 5, 2, 1, 1, 1, 1, NA, NA, 4, 3, 4, 3, 5, 3…
$ UI01_01 <ord> 5, 4, 4, 5, 4, 5, 5, 5, 3, 5, 5, 3, 5, 5, …
$ UI01_03 <ord> 5, 3, NA, NA, 4, NA, NA, 4, 3, 5, 2, 3, 5,…
$ UI01_04 <ord> 5, 2, 1, 1, 1, 1, NA, NA, 2, 1, 1, 3, 5, 2…
$ EX01_01 <ord> 5, 4, 3, 3, NA, 2, NA, 5, 4, 4, 4, 3, 5, 3…
$ EX01_02 <ord> 5, 2, 3, 1, 4, 2, NA, 2, 2, 2, 2, 3, 5, 5,…
$ EX01_03 <ord> 5, 1, 3, 1, NA, 2, NA, 2, 2, 1, 1, 3, 5, 3…
$ EX01_04 <ord> 5, 1, 1, 1, 1, 2, 4, 1, 4, NA, 4, 3, 4, 5,…
$ STARTED <dttm> 2025-09-26 14:11:10, 2025-09-26 15:13:01,…
$ LASTDATA <dttm> 2025-09-26 14:16:16, 2025-09-26 15:21:43,…
$ TIME_SUM <dbl> 306, 430, 369, 555, 445, 309, 749, 318, 27…
$ FINISHED <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
$ .imp <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ .id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,…
$ total_score_imputed_items <dbl> 5.000000, 2.500000, 2.846154, 2.461538, 2.…The adjusted pilot containing the total score is transformed back into a mids object for analyzing the FMI tendency across all imputed items. As we are not inspecting the items on category level but on a macro measurement scale level, we can use continuous parametric methods, such as “lm()” (Carifio and Perla, 2007). Using the general linear model (GLM) we can estimate the FMI on the basis of socio demographics and time-related information.
pilot_adjusted <- as.mids(pilot_extracted_mutated)
pilot_fit <- with(pilot_adjusted, lm(total_score_imputed_items ~ TR01 + SD01 + SD02 + SD04 + SD05 + TIME_SUM))
pilot_est <- pool(pilot_fit)
pilot_est$pooledAs the intercept FMI of the pilot imputation is ≈0.016 the m must not be increased as the FMI is low. The “ubar” value which is the within-imputation variance indicates a rather low sampling variability. “b” which is the between imputation variance is 0, i.e., the estimation variability due to missing data is not given. This could be due to the underlying structure of the score which ordinal per item and thus, only approximately continuous. In total these two rather low values indicate that the MI is efficient already and reinforce our assumption that the m value must not be increased further. (Von Hippel, 2018)
summary(pilot_est, conf.int = TRUE) term estimate std.error statistic df p.value
1 (Intercept) 3.1709380520 0.3340908342 9.4912453 122.035 2.450065e-16
2 TR01 0.3800394130 0.0448194833 8.4793350 122.035 6.203517e-14
3 SD01 -0.0709869155 0.1004683346 -0.7065601 122.035 4.811868e-01
4 SD02 0.0109380627 0.0191674556 0.5706580 122.035 5.692808e-01
5 SD04 -0.0829659963 0.0194851490 -4.2579092 122.035 4.077719e-05
6 SD05 0.0262467493 0.0745291321 0.3521676 122.035 7.253200e-01
7 TIME_SUM -0.0001903381 0.0002062236 -0.9229692 122.035 3.578445e-01
2.5 % 97.5 % conf.low conf.high
1 2.5095737783 3.832302326 2.5095737783 3.832302326
2 0.2913150244 0.468763802 0.2913150244 0.468763802
3 -0.2698734468 0.127899616 -0.2698734468 0.127899616
4 -0.0270057210 0.048881846 -0.0270057210 0.048881846
5 -0.1215386842 -0.044393309 -0.1215386842 -0.044393309
6 -0.1212906875 0.173784186 -0.1212906875 0.173784186
7 -0.0005985772 0.000217901 -0.0005985772 0.000217901To achieve a final clarification if the current MI is sufficient, the SE has to be analyzed. Against the backdrop of the tiny sample size of 131 as well as the low share of NA values and consequently, the low FMI - the SE is with ≈0.33 near 0, too. The SE might only decrease further with an increasing sample size (Kaltenbach, 2021), as the FMI is significantly lower than 0.5 whereas an increase of the m would not decrease the SE nor the FMI significantly (Von Hippel, 2018). The Monte Carlo error, which depicts the deviations between the m imputations, is expected to be 0 according to the formula of White et al. (2010) as the between imputation variance “b” is 0.
Consequently, a Monte Carlo simulation would not achieve a significant explanatory contribution is not conducted in this evaluation (Schunk, 2008). This leads us to the conclusion that the pilot MI is already sufficient. Thus, we are exporting the mids object in its original format as well as a .csv for reusability for ordinal CFA and (M)ANOVA.
# mids object
saveRDS(pilot_imp, "data/mi_mids_object.rds")
# csv depicting the mids object
final_imputed_dataset <- complete(pilot_imp, include = TRUE, action = "long")
write.csv(final_imputed_dataset, "data/mi_dataset.csv", row.names = FALSE)
Latex Export
xtable::xtable(df_na, type = "latex")% latex table generated in R 4.5.1 by xtable 1.8-4 package
% Tue Dec 9 12:20:47 2025
\begin{table}[ht]
\centering
\begin{tabular}{rlrr}
\hline
& item & absolute\_amount\_of\_NA & relative\_amount\_of\_NA \\
\hline
1 & AC01\_01 & 3 & 2.29 \\
2 & AC01\_02 & 25 & 19.08 \\
3 & AC01\_03 & 4 & 3.05 \\
4 & DI01\_01 & 9 & 6.87 \\
5 & DI01\_02 & 9 & 6.87 \\
6 & DI01\_03 & 11 & 8.40 \\
7 & DI01\_04 & 4 & 3.05 \\
8 & UI01\_01 & 2 & 1.53 \\
9 & UI01\_02 & 0 & 0.00 \\
10 & UI01\_03 & 38 & 29.01 \\
11 & UI01\_04 & 8 & 6.11 \\
12 & EX01\_01 & 9 & 6.87 \\
13 & EX01\_02 & 6 & 4.58 \\
14 & EX01\_03 & 12 & 9.16 \\
15 & EX01\_04 & 6 & 4.58 \\
\hline
\end{tabular}
\end{table}Appendix of Multiple Imputation
To test whether the previous stated argumentation is true, another MI is conducted with a larger m and more iterations. As the values speak for themselves, and the focus of the thesis is not on statistics, this is not further examined.
set.seed(1002)
quality_check <- mice(draft_data, predictorMatrix = predictorMatrix, maxit = 25, method = ini_meth, m = 25, seed = 1002)
iter imp variable
1 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
1 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
2 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
3 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
4 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
5 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
6 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
7 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
8 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
9 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
10 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
11 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
12 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
13 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
14 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
15 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
16 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
17 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
18 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
19 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
20 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
21 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
22 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
23 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
24 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 1 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 2 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 3 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 4 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 5 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 6 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 7 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 8 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 9 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 10 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 11 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 12 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 13 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 14 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 15 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 16 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 17 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 18 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 19 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 20 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 21 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 22 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 23 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 24 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04
25 25 AC01_01 AC01_02 AC01_03 DI01_01 DI01_02 DI01_03 DI01_04 UI01_01 UI01_03 UI01_04 EX01_01 EX01_02 EX01_03 EX01_04Check for convergence:
plot(quality_check, c(relevant_imputed_col))
Density check:
vars <- relevant_imputed_col
stripplot(quality_check, as.formula(paste("~", paste(vars, collapse = " + "))), layout = c(1, 1), xlim = c(0, 6))
FMI check:
quality_check_extracted <- complete(quality_check, include = TRUE, action = "long")
quality_check_extracted$UI01_02 <- NULL
quality_checkt_extracted_mutated <- quality_check_extracted %>%
mutate(
across(
all_of(relevant_imputed_col), ~as.integer(.x)
)
)
quality_checkt_extracted_mutated <- quality_check_extracted %>%
mutate(
total_score_imputed_items =
rowMeans(
quality_checkt_extracted_mutated[, (relevant_imputed_col)], na.rm = TRUE
)
)
glimpse(quality_checkt_extracted_mutated)Rows: 3,406
Columns: 28
$ `NEW CASE NR` <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,…
$ SD01 <dbl> 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, …
$ SD02 <dbl> 11, 2, 2, 5, 2, 8, 5, 2, 3, 4, 2, 2, 2, 1,…
$ SD04 <dbl> 5, 7, 6, 11, 10, 6, 5, 10, 9, 11, 10, 9, 6…
$ SD05 <dbl> 7, 2, 6, 5, 4, 4, 4, 4, 6, 4, 4, 4, 2, 1, …
$ TR01_CP <dbl> 2, 2, 3, 3, 4, 4, 5, 5, 5, 6, 6, 6, 7, 8, …
$ TR01 <dbl> 3, 2, 1, 2, 2, 1, 4, 1, 3, 2, 4, 1, 1, 2, …
$ AC01_01 <ord> 5, 4, 5, 5, 5, 5, 4, 5, 4, 3, 4, 3, 5, 4, …
$ AC01_02 <ord> 5, 4, 5, 4, 5, 4, NA, 4, 4, 4, 4, 3, 4, 5,…
$ AC01_03 <ord> 5, 4, 5, 4, 2, 5, 4, 5, 4, 4, 3, 3, 5, 4, …
$ DI01_01 <ord> 5, 2, 4, 4, 3, 5, 4, 4, NA, 5, 3, 3, 5, 5,…
$ DI01_02 <ord> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 4, 3, 5, 4…
$ DI01_03 <ord> 5, 1, 1, 1, 1, 1, 5, NA, 5, NA, 5, 3, 5, N…
$ DI01_04 <ord> 5, 2, 1, 1, 1, 1, NA, NA, 4, 3, 4, 3, 5, 3…
$ UI01_01 <ord> 5, 4, 4, 5, 4, 5, 5, 5, 3, 5, 5, 3, 5, 5, …
$ UI01_03 <ord> 5, 3, NA, NA, 4, NA, NA, 4, 3, 5, 2, 3, 5,…
$ UI01_04 <ord> 5, 2, 1, 1, 1, 1, NA, NA, 2, 1, 1, 3, 5, 2…
$ EX01_01 <ord> 5, 4, 3, 3, NA, 2, NA, 5, 4, 4, 4, 3, 5, 3…
$ EX01_02 <ord> 5, 2, 3, 1, 4, 2, NA, 2, 2, 2, 2, 3, 5, 5,…
$ EX01_03 <ord> 5, 1, 3, 1, NA, 2, NA, 2, 2, 1, 1, 3, 5, 3…
$ EX01_04 <ord> 5, 1, 1, 1, 1, 2, 4, 1, 4, NA, 4, 3, 4, 5,…
$ STARTED <dttm> 2025-09-26 14:11:10, 2025-09-26 15:13:01,…
$ LASTDATA <dttm> 2025-09-26 14:16:16, 2025-09-26 15:21:43,…
$ TIME_SUM <dbl> 306, 430, 369, 555, 445, 309, 749, 318, 27…
$ FINISHED <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
$ .imp <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ .id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,…
$ total_score_imputed_items <dbl> 5.000000, 2.500000, 2.846154, 2.461538, 2.…FMI analysis:
quality_check_adjusted <- as.mids(quality_checkt_extracted_mutated)
quality_check_fit <- with(quality_check_adjusted, lm(total_score_imputed_items ~ TR01 + SD01 + SD02 + SD04 + SD05 + TIME_SUM))
quality_check_est <- pool(quality_check_fit)
quality_check_est$pooledsummary(quality_check_est, conf.int = TRUE) term estimate std.error statistic df p.value
1 (Intercept) 3.1709380520 0.3340908342 9.4912453 122.035 2.450063e-16
2 TR01 0.3800394130 0.0448194833 8.4793350 122.035 6.203514e-14
3 SD01 -0.0709869155 0.1004683346 -0.7065601 122.035 4.811868e-01
4 SD02 0.0109380627 0.0191674556 0.5706580 122.035 5.692808e-01
5 SD04 -0.0829659963 0.0194851490 -4.2579092 122.035 4.077719e-05
6 SD05 0.0262467493 0.0745291321 0.3521676 122.035 7.253200e-01
7 TIME_SUM -0.0001903381 0.0002062236 -0.9229692 122.035 3.578445e-01
2.5 % 97.5 % conf.low conf.high
1 2.5095737789 3.832302325 2.5095737789 3.832302325
2 0.2913150245 0.468763801 0.2913150245 0.468763801
3 -0.2698734467 0.127899616 -0.2698734467 0.127899616
4 -0.0270057209 0.048881846 -0.0270057209 0.048881846
5 -0.1215386841 -0.044393309 -0.1215386841 -0.044393309
6 -0.1212906873 0.173784186 -0.1212906873 0.173784186
7 -0.0005985772 0.000217901 -0.0005985772 0.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